Secondly, the non-convex regularized fused lasso (FL) approach proposed in [1]} is adopted,
which is an improved version of conventional FL [2]},
allowing one regularizer to be non-convex and preserving the global convexity.
The result is shown in Figure REF (b).
Thirdly, group-sparse signal denoising (GSSD) also known as OGS with non-convex regularization [3]}
is adopted.
More specifically, `atan' penalty with group size to be 3 samples is used,
and the regularization parameter is chosen to optimize the RMSE.
The result is shown in Figure REF (c).
Both of the above methods also have worse recoveries in terms of RMSE.
In addition, these methods are all denoising methods only,
they cannot decompose the signal into two distinct sequences of transients, each exhibiting its own period.
